class_docstr: Main network which does cross-lingual embeddings training
docstr: Drops learning rate based on CSLS criterion
  Arguments:
      local_lr(float): Learning Rate
      drop_lr(bool): Drop learning rate by 2 if True
docstr_tok: ["Drops","learning","rate","based","on","CSLS","criterion","Arguments",":","local_lr","(","float",")",":","Learning","Rate","drop_lr","(","bool",")",":","Drop","learning","rate","by","2","if","True"]
code: def set_lr(local_lr, drop_lr):
      """
      Drops learning rate based on CSLS criterion
      Arguments:
          local_lr(float): Learning Rate
          drop_lr(bool): Drop learning rate by 2 if True
      """
      new_lr = local_lr * 0.98
      print(
          "Dropping learning rate to "
          + str(new_lr)
          + " from "
          + str(local_lr)
      )
      if drop_lr:
          new_lr = new_lr / 2.0
          print(
              "Dividing learning rate by 2 as validation criterion\
                     decreased. New lr is "
              + str(new_lr)
          )
      return new_lr
  
imports: from __future__ import print_function, division
  import io
  import os
  import time
  import numpy
  import scipy
  import tensorflow
label_desc: Use image node_id 8 for calling the WordTranslator obj's underlying member method code with example usage: obj.set_lr(local_lr, drop_lr) and returns: new_lr